Introduction To Statistical Data Analysis For The Life Sciences - Ekstrom Claus Thorn; Sørensen Helle | Libro Chapman And Hall/Crc 12/2014 - HOEPLI.it


home libri books ebook dvd e film top ten sconti 0 Carrello


Torna Indietro

ekstrom claus thorn; sørensen helle - introduction to statistical data analysis for the life sciences

Introduction to Statistical Data Analysis for the Life Sciences

;




Disponibilità: Normalmente disponibile in 20 giorni
A causa di problematiche nell'approvvigionamento legate alla Brexit sono possibili ritardi nelle consegne.


PREZZO
62,98 €
NICEPRICE
59,83 €
SCONTO
5%



Questo prodotto usufruisce delle SPEDIZIONI GRATIS
selezionando l'opzione Corriere Veloce in fase di ordine.


Pagabile anche con 18App Bonus Cultura e Carta del Docente


Facebook Twitter Aggiungi commento


Spese Gratis

Dettagli

Genere:Libro
Lingua: Inglese
Pubblicazione: 12/2014
Edizione: Edizione nuova, 2° edizione





Note Editore

A Hands-On Approach to Teaching Introductory Statistics

Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets.

New to the Second Edition

  • A new chapter on non-linear regression models
  • A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken
  • Additional exercises in most chapters
  • A summary of statistical formulas related to the specific designs used to teach the statistical concepts

This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.





Sommario

Description of Samples and Populations
Data types
Visualizing categorical data
Visualizing quantitative data
Statistical summaries
What is a probability?
R

Linear Regression
Fitting a regression line
When is linear regression appropriate?
The correlation coefficient
Perspective
R

Comparison of Groups
Graphical and simple numerical comparison
Between-group variation and within-group variation
Populations, samples, and expected values
Least squares estimation and residuals
Paired and unpaired samples
Perspective
R

The Normal Distribution
Properties
One sample
Are the data (approximately) normally distributed?
The central limit theorem
R

Statistical Models, Estimation, and Confidence Intervals
Statistical models
Estimation
Confidence intervals
Unpaired samples with different standard deviations
R

Hypothesis Tests
Null hypotheses
t-tests
Tests in a one-way ANOVA
Hypothesis tests as comparison of nested models
Type I and type II errors
R

Model Validation and Prediction
Model validation
Prediction
R

Linear Normal Models
Multiple linear regression
Additive two-way analysis of variance
Linear models
Interactions between variables
R

Non-Linear Regression
Non-linear regression models
Estimation, confidence intervals, and hypothesis tests
Model validation
R

Probabilities
Outcomes, events, and probabilities
Conditional probabilities
Independence

The Binomial Distribution
The independent trials model
The binomial distribution
Estimation, confidence intervals, and hypothesis tests
Differences between proportions
R

Analysis of Count Data
The chi-square test for goodness-of-fit
2 x 2 contingency table
Two-sided contingency tables
R

Logistic Regression
Odds and odds ratios
Logistic regression models
Estimation and confidence intervals
Hypothesis tests
Model validation and prediction
R

Statistical Analysis Examples
Water temperature and frequency of electric signals from electric eels
Association between listeria growth and RIP2 protein
Degradation of dioxin
Effect of an inhibitor on the chemical reaction rate
Birthday bulge on the Danish soccer team
Animal welfare
Monitoring herbicide efficacy

Case Exercises
Case 1: Linear modeling
Case 2: Data transformations
Case 3: Two sample comparisons
Case 4: Linear regression with and without intercept
Case 5: Analysis of variance and test for linear trend
Case 6: Regression modeling and transformations
Case 7: Linear models
Case 8: Binary variables
Case 9: Agreement
Case 10: Logistic regression
Case 11: Non-linear regression
Case 12: Power and sample size calculations

Appendix A: Summary of Inference Methods
Appendix B: Introduction to R
Appendix C: Statistical Tables
Appendix D: List of Examples Used throughout the Book

Bibliography

Index

Exercises appear at the end of each chapter.








Altre Informazioni

ISBN:

9781482238938

Condizione: Nuovo
Dimensioni: 9.25 x 6.125 in Ø 1.65 lb
Formato: Brossura
Illustration Notes:101 b/w images, 97 tables and 10/15 INKJET REPRINT
Pagine Arabe: 526






Utilizziamo i cookie di profilazione, anche di terze parti, per migliorare la navigazione, per fornire servizi e proporti pubblicità in linea con le tue preferenze. Se vuoi saperne di più o negare il consenso a tutti o ad alcuni cookie clicca qui. Chiudendo questo banner o proseguendo nella navigazione acconsenti all’uso dei cookie.

X